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An Improved Method to Assess the Value of Assuring Limited Local Electric Service in the Event of Major Grid Outages

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posted on 06.09.2018, 00:00 authored by Sun Hee BaikSun Hee Baik
America's dependence on reliable electric power, and our individual and collective vulnerability
to power disruption, continues to grow. While it would be technically possible to make changes
that could sustain many critical electricity-dependent services during widespread and longlasting
outages by implementing smart grid technologies, distributed generation resources, and
other technologies, these technologies would require incremental investments where the benefits
are uncertain and difficult to quantify in many cases.
For many years, distribution utilities in United States have conducted studies of the value that
customers place on reliable electric services. However, these studies and associated literature
suffer from several shortcomings: they have not devoted much effort to help respondents fully
understand and consider the various implications of hypothetical outages that respondents may
not have experienced nor previously considered; they have done little to minimize cognitive
biases; they have focused almost exclusively on brief outages that last only up to a few hours;
and, they have only considered the difference between full backup service and no service. Hence,
their results are not adequate to assess how much individuals or society might, or should, be
willing to avoid longer outages or provide full or limited backup service in the event of large
outages of long duration.
To address these issues, we have developed and demonstrated a set of improved methods that
help residential customers think systematically about the value they attach to reliable electric
service and have used the elicited informed judgments to illustrate how the results could be used
for local or regional-decision-making.
After introducing the issues in Chapter 1, Chapter 2 summarizes a new elicitation framework that
has been designed to help residential electricity customers think carefully about the value they attach to reliable electric service. The survey framework was applied to a convenience sample of
residents in Allegheny County, Pennsylvania to assess their willingness-to-pay to receive backup
services during a hypothetical 24-hour outage on a hot summer day. The face-to-face interview
results suggest that there exists a considerable amount of consumer surplus associated with
providing partial electric backup service (i.e., the respondents’ willingness-to-pay per kWh is
significantly higher for their first bit of electricity than the value of the last amount consumed).
Further, the assessed value of sustaining demands the respondents assessed to be high priority
significantly increased as they receive additional information and better understood the outage
scenario and its consequences.
In Chapter 3, we estimated the cost to implement to implement the capability to provide limited
emergency backup power service using isolated distribution feeders, evenly distributed the
incremental investment costs across to all residential customers across outages, compared the
required service payment with the measured willingness-to-pay distribution, and explored
whether and when such investments can be justified. We first conducted a series of order of
magnitude calculations and found that providing the low-amperage backup service can be more
cost-effective than buying a small portable generator and storing diesel or gasoline for refueling
even if a 24-long outage occurs once every 20 years, and the backup service appears to be more
cost-effective if a region is expected to suffer more frequent and longer outages. In addition to
the assessments using private willingness-to-pay, the chapter also considers two methods that
might be used to recover system upgrade costs without raising a serious equity issue nor
imposing an excessive burden to either residential customers or the region.
In order to explore respondents’ willingness-to-pay under a variety of scenarios for different
geographical regions more efficiently, the face-to-face survey framework has been modified for online use. Chapter 4 first describes the details of the generalizable web-based survey framework
that a researcher or decision-maker can use to design ones’ own outage scenarios. It also
addresses several factors that are assumed to influence estimates from stated preference valuation
studies. The framework was then used to elicit the economic and social preferences for reliable
electric backup services during hypothetical 10-day widespread outages from a sample of
residents of the Northeastern United States. We first demonstrated the importance of helping
respondents fully consider the various aspects of the consequences of the hypothetical outages
and better articulate their values, and then used the elicited preferences to explore whether and
how much some of the factors that are known to affect respondents’ risk perceptions influence
their willingness-to-pay values for reliable electric services during the hypothetical outages. The
chapter concludes with a discussion of why exploring preferences for reliable electric services
under a variety of scenarios and constructing customer damage functions for electricity
customers are important, and what we see as future behavioral research needs.
Finally, in Chapter 5, we discussed how the elicited preferences can be used to make more
informed and collective societal decisions. Benefit-cost analysis and other forms of analysis have
been widely used in policy analysis and government decision-making. However, only
uncertainties about costs and physical states of the world are considered, neglecting uncertainty
about the level of benefits that come from the value the public places on policy outcomes. In this
chapter, we proposed such an approach that incorporates uncertainties in individual preferences.
Using the public valuations of implementing smart grid technologies to mitigate impacts of
large-regional outages, we showed uncertainty in individual preferences, when aggregated to
form societal preference intervals, can substantially change the decision society would make.

History

Date

06/09/2018

Degree Type

Dissertation

Department

Engineering and Public Policy

Degree Name

  • Doctor of Philosophy (PhD)

Advisor(s)

M. Granger Morgan Alexander L. Davis